Study of enterprise management training based on cluster computing

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Abstract

This paper studies the training of enterprise personnel recruitment management based on cluster computing. The study is mainly from the Angle of employment recommendation. First of all, this paper makes full use of the college graduates and the previous employment data, a sensitive-personal rank algorithm is proposed to calculate the interest sensitivity of different enterprises in the history recruitment data. Secondly, the sensitivity of enterprise interest is combined to improve the correlation calculation method between fresh graduates and previous graduates. Finally, the correlation results are combined with the trust of enterprises, and the employment of similar former graduates is recommended to fresh graduates, providing reference and guidance for their employment. The experimental result shows that RBSI achieves high recommendation accuracy and satisfaction.

Keywords

Cluster computing Personnel training Sensitive-personal rank algorithm 

References

  1. 1.
    De Myttenaere, A., Golden, B., Grand, B.L., et al.: Study of a bias in the offline evaluation of a recommendation algorithm. Comput. Sci. 79(3), 263–272 (2015)Google Scholar
  2. 2.
    Cheng, J., Liu, Y., Zhang, H., et al.: A new recommendation algorithm based on user’s dynamic information in complex social network. Math. Probl. Eng. 20(9), 1–6 (2015)Google Scholar
  3. 3.
    Azadeh, A., Bonab, N.A., Salehi, V., et al.: A unique algorithm for the assessment and improvement of job satisfaction by resilience engineering: hazardous labs. Int. J. Ind. Ergon. 49(1), 68–77 (2015)CrossRefGoogle Scholar
  4. 4.
    Palacios, J.J., González-Rodríguez, I., Vela, C.R., et al.: Coevolutionary makespan optimisation through different ranking methods for the fuzzy flexible job shop. Fuzzy Sets Syst. 278, 81–97 (2015)MathSciNetCrossRefMATHGoogle Scholar
  5. 5.
    Gaborit, P., Ruatta, O., Schrek, J., et al.: RankSign: an efficient signature algorithm based on the rank metric. Fuzzy Sets Syst. 8772, 88–107 (2016)MathSciNetMATHGoogle Scholar
  6. 6.
    Nan, F., Chu, Y., Huo, W.: Applied study of markov chain model on employment guidance quality evaluation. Tech. Bull. 55(12), 152–157 (2017)Google Scholar
  7. 7.
    Huang, G.H.: A Study on the evaluation model of the tourism industry cluster based on factor analysis. J. Appl. Stat. Manage. 1(12), 77–81 (2017)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Tianjin Sino-German University of Applied SciencesTianjinChina

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